关键词: SAR图像, 水体提取, 降斑各向异性扩散, 最大类间方差, 连通域标定

Abstract:

The use of remote sensing technology to obtain surface waterbody information is of great significance for water resource investigation, natural disaster assessment, watershed planning, and ecological environment monitoring. As a reliable data source for large-scale ground monitoring, SAR imaging has unique advantages that optical remote sensing systems of all-weather, all-weather, and wide coverage do not have, and has been widely used in waterbody mapping. However, due to the influence of speckle noise of SAR imagery, existing methods for waterbody mapping are difficult to extract the complex and fine natural water structures from SAR imagery quickly and accurately. In this paper, a new waterbody extraction method for SAR imagery based on improved speckle reducing anisotropic diffusion and maximum between-cluster variance was proposed. First, the SAR imagery were filtered by improved speckle reducing anisotropic diffusion. The iterative process was adaptively controlled by calculating the average structural similarity between imagery in the iterative filtering process, so that the fine edges and texture structure could be preserved simultaneously. Then, based on the criterion of maximum variance between classes, the threshold value was determined adaptively, and the binary segmentation of the filtered image was conducted. In the binarized segmentation result, connected foreground regions composed of the pixel points that have same intensity values and adjoin to each other spatially, are searched. In so doing, each connected region formed an identified block. By obtaining geometric parameters of these blocks, the false segmentation of the imagery was eliminated, and real waterbody areas were precisely identified based on the SAR imagery. To verify the accuracy of the proposed method, water boundaries extracted by this method were on manually drawn waterbody boundaries. Results of comparing the two methods show that they are pretty consistent with each other. Meanwhile, the results of our proposed method were compared with the results of three other kinds of water extraction algorithms commonly used for SAR imagery, in terms of the visual level, extraction accuracy, and running time. The running time of the proposed method meets the requirement of real-time application. The overlap degree of the extracted boundary in two pixels rating areas has reached 80%, which is obviously superior to other methods and the extraction results of the proposed method are also more significant in visual aspects such as boundary and detail information. The qualitative and quantitative evaluation shows the superiority of our proposed method.

Key words: SAR imagery, waterbody extraction, speckle reducing anisotropic diffusion, maximum between-cluster variance, connected-domain calibration